The impact of interest rate and its volatility on banking sector development empirical evidence from southeast asia 2022

MINISTRY OF EDUCATION TRAINING STATE BANK OF VIET NAM BANKING UNIVERSITY OF HO CHI MINH CITY  TRẦN NGỌC THANH THỦY THE IMPACT OF INTEREST RATE AND ITS VOLATILITY ON BANKING SECTOR DEVELOPMENT EMP.

MINISTRY OF EDUCATION & TRAINING STATE BANK OF VIET NAM

BANKING UNIVERSITY OF HO CHI MINH CITY

CODE: 7340201

HO CHI MINH CITY, 2022

MINISTRY OF EDUCATION & TRAINING STATE BANK OF VIET NAM

BANKING UNIVERSITY OF HO CHI MINH CITY

CODE: 7340201

SUPERVISOR NGUYỄN DUY LINH, Ph.D

HO CHI MINH CITY, 2022

COMMENTS OF THE SUPERVISOR

Ho Chi Minh city, …/… /2022

Supervisor

Ph.D Nguyễn Duy Linh

ABSTRACT

For all economies, especially in the countries of Southeast Asia, the banking system plays a very important role in the movement and supply of capital in the economy For macroeconomic activities, the interest rate is one of the crucial tools

to control and regulate the market to stabilize and promote economic growth Because of these reasons, this thesis examines the relationship between interest rate, interest rate volatility, and banking sector development of countries in Southeast Asia including Indonesia, Malaysia, Myanmar, Singapore, and Vietnam from 1996

to 2020

The thesis utilizes the main method of quantitative research as the basis for the topic The author manipulates a variety of regression methods including Pooled OLS, FEM, REM and FGLS Experimental results from running the model and the tests will be used as a basis for accepting or rejecting the research hypotheses, ensuring the appropriateness of the model

Empirical results show that all indicators of the banking industry receive a positive impact from interest rates, at the same time, this connection also becomes weaker when interest rates are lower because of the convex relationship between interest rates and the development of the banking industry In addition, the empirical results supply evidence that interest rate volatility has a negative impact

on several banking sector development indicators, implying that the banking sector

of the sample is susceptible to interest rate risk Moreover, all indicators of the banking industry are negatively affected by GDP Finally, for the banking system and policymakers, these findings have important implications for strengthening the banking sector and promoting economic growth in these countries

COMMITMENT

I thus certify that my thesis "The impact of interest rate and its volatility

on banking sector development: Empirical evidence from Southeast Asia" is

my own research work, conducted under the supervision of Dr Nguyen Duy Linh after a rigorous working procedure The research findings are trustworthy since they are free of already published or created other content, with the exception of fully cited sources in the thesis

I assume full responsibility for my commitment

Ho Chi Minh City, ……… 2022

Author

Trần Ngọc Thanh Thủy

I would also like to express my gratitude to Dr Nguyen Duy Linh, who went above and beyond to assist me and create the finest possible conditions for me to complete my graduation thesis

Moreover, I want to convey my gratitude to my family and friends for their encouragement and support as I worked on this thesis

Because of the constraints of knowledge, flaws are unavoidable during the thesis writing process I look forward to receiving comments and suggestions in order to make the topic more complete, and at the same time create a better foundation for future research

Thank you sincerely!

Ho Chi Minh City, ……… 2022

Author

Trần Ngọc Thanh Thủy

TABLE OF CONTENTS

ABSTRACT i

COMMITMENT ii

ACKNOWLEDGEMENTS iii

TABLE OF CONTENTS iv

LIST OF ABBREVIATIONS viii

LIST OF TABLES AND FIGURES ix

CHAPTER 1 INTRODUCTION 1

1.1 REASONS FOR CHOOSING THE TOPIC 1

1.2 RESEARCH OBJECTIVES AND QUESTIONS 3

1.2.1 Overall research objective 3

1.2.2 Specific research objectives 3

1.2.3 Research questions 4

1.3 RESEARCH SCOPE AND SUBJECT 4

1.3.1 Research subject 4

1.3.2 Research scope 4

1.4 RESEARCH METHODOLOGY 5

1.5 NEW CONTRIBUTIONS OF THE STUDY 6

1.5.1 Research gap 6

1.5.2 New contributions 7

1.6 FRAMEWORK OF THE RESEARCH PROCESS 8

1.7 STRUCTURE OF THE RESEARCH 8

CHAPTER 2 THEORETICAL BASIS AND OVERVIEW OF RELATED

STUDIES 10

2.1 THEORETICAL BASIS OF INTEREST RATE, INTEREST RATE VOLATILITY, AND BANKING SECTOR DEVELOPMENT 10

2.1.1 Concept of interest rate 10

2.1.2 Concept of interest rate volatility 12

2.1.3 The relationship between interest rate and different aspects of the banking industry 13

2.1.4 The relationship between interest rate volatility and banking sector development (BSD) 15

2.2 THEORETICAL BACKGROUND 15

2.2.1 Classical Theory of Interest 15

2.2.2 Liquidity Preference Theory of Interest 16

2.2.3 Loanable funds theory 18

2.3 THE RELEVANT EMPIRICAL STUDIES 19

2.3.1 Vietnamese researches 20

2.3.2 English researches 20

CONCLUSION OF CHAPTER 2 25

CHAPTER 3 RESEARCH METHODOLOGY 26

3.1 DATA SOURCE 26

3.2 DESCRIPTION OF VARIABLE 27

3.2.1 Dependent variable 28

3.2.2 Explanatory variable 30

3.2.3 Control variable 33

3.3 RESEARCH MODEL AND ECONOMETRIC METHODOLOGY 34

3.4 RESEARCH PROCESS 36

3.5 RESEARCH METHODS 37

CONCLUSION OF CHAPTER 3 39

CHAPTER 4 EMPIRICAL RESULTS AND DISCUSSION 40

4.1 PANEL UNIT-ROOT TESTS 40

4.2 DESCRIPTIVE STATISTICS 43

4.3 CORRELATION COEFFICIENT MATRIX 46

4.4 MULTICOLLINEARITY TEST 47

4.5 REGRESSION RESULTS 48

4.5.1 Regression results with FEM method 48

4.5.2 Regression results with REM method 49

4.5.3 Regression results with pooled OLS estimator 51

4.5.4 Regression results with FGLS estimator 54

CONCLUSION OF CHAPTER 4 58

CHAPTER 5 CONCLUSIONS AND RECOMMENDATIONS 59

5.1 CONCLUSIONS 59

5.2 RECOMMENDATIONS 61

5.2.1 For the banking sector in the sample countries 61

5.2.2 For interest rate policymakers 62

5.3 LIMITATIONS AND FUTURE RESEARCH DIRECTIONS OF THE STUDY 63

5.3.1 Limitations of the study 63

5.3.2 Future research directions 64

CONCLUSION OF CHAPTER 5 65

REFERENCES 66 APPENDIX 74 Appendix 1: Creating “Index” by using the principal component analysis (PCA) method 74 Appendix 2: Panel Unit-root Tests 75 Appendix 3: Descriptive statistic 78 Appendix 4: Regression of the model following Pooled OLS, FEM, REM 79 Appendix 5: Model selection test Pooled OLS, FEM, REM 81 Appendix 6: FGLS method 84

LIST OF ABBREVIATIONS

1 ARDL Autoregressive Distributed Lag

4 BSD Banking sector development

7 FGLS Feasible Generalized Least Squares

9 IPS Im-Pesaran–Shin test

11 LLC Levin-Lin-Chu test

12 OLS Ordinary Least Squares

14 PCA Principal Component Analysis

15 RATE Real-time deposit interest rates

17 RATE_SQ Quadratic term for the interest rate

19 VIF Variance Inflation Factor

20 VR Interest rate volatility

LIST OF TABLES AND FIGURES

Table 3.1 List of countries used in the research 27

Table 3.2 Summary of variables 34

Table 4.1 Panel Unit-root Test Results 42

Table 4.2 Descriptive statistics 45

Table 4.3 Correlation coefficient matrix 46

Table 4.4 Multicollinearity test results 47

Table 4.5 Regression results by FEM 49

Table 4.6 Regression results by REM 50

Table 4.7 Regression results by pooled OLS method 52

Table 4.8 The result of testing homoskedasticity 53

Table 4.9 The result of testing autocorrelation 54

Table 4.10 Regression results by FGLS method 55

Figure 2.1 Classical Theory of Interest 16

Figure 2.2 Function of Liquidity Preference Theory of Interest 17

Figure 2.3 Loanable funds theory graph 18

Figure 3.1 The relationship between variable types 28

Figure 3.2 Design of research process 36

CHAPTER 1 INTRODUCTION

The purpose of this chapter is to present the thesis's main idea The necessity

of conducting the research is stated at the beginning of the document, and the author will highlight the study's importance and objectives The author next selects and employs suitable research methods after determining the research topic, research object, and research scope The contributions and the research content of the topic will be presented in this chapter

1.1 REASONS FOR CHOOSING THE TOPIC

The banking sector's importance in an economy is undeniable A healthy banking sector is a necessary and inextricable component of economic growth According to financial development literature, countries with well-developed banking systems have higher economic growth rates (Beck et al., 2000; King and Levine, 1993; Levine, 2005a,b; Levine et al., 2000; Levine and Zeroes, 1998)

One of the most important macroeconomic variables, the interest rate, is closely linked to the development of the banking sector and economic growth The banking sector is influenced by interest rates in a variety of ways Indeed, higher deposit interest rates encourage investors to shift their funds from other investment instruments to bank deposits, enhancing the banking sector's ability to support economic activities On the other hand, increasing deposit interest rates boosts the cost of banks' surplus reserves, which rises lending interest rates and lowers economic investment activity, and vice versa (Alam and Uddin, 2009) As a result, interest rate variations have an impact on the number of banking transactions, thereby significantly affecting the level of development of the banking sector Furthermore, Mankiw (1986) demonstrated that interest rate volatility can alter the quality of a bank's loan portfolio: a rise in the lending interest rate reduces the demand for credit from high-quality creditors while raising the demand for credit from low-quality creditors This could result in banks being targeted for adverse

selection, which would negatively influence their market value As a result, interest rate volatility might potentially hinder the banking sector's crucial role in encouraging economic growth

The impact of interest rate levels and changes on the banking business has been extensively researched in the financial literature from diverse angles The sensitivity of a bank's assets and liabilities to interest rate variations, for instance, can have an impact on the banking sector Because of the duration mismatch between a bank's assets and its liabilities, such effects could be magnified (Joseph and Vezos, 2006; Papadamou and Siriopoulos, 2014) Furthermore, interest rates have a considerable impact on the costs and profits of financial organizations As a result, interest rate volatility could have an impact on the banking industry via cost and revenue channels (Saunders and Yourougou, 1990; Tripathi and Ghosh, 2012) Furthermore, frictions in the credit market can lead to fluctuations in interest rates, adversely affecting the banking sector's performance, and undermining the banking sector's profitability (Huybens and Smith, 1999)

Interest rate movements have been recorded in recent decades to reflect changes in the financial environment, such as changes in the monetary policy regimes, financial innovations, and financial market integration (Elyasiani and Mansur, 1998) This study examines the impact of interest rates and interest rate volatility on banking sector development (BSD) indicators in five Southeast Asian nations, including Indonesia, Malaysia, Myanmar, Singapore and Vietnam, from

1996 to the end of 2020

Over the last few decades, countries such as Singapore, Malaysia, and Indonesia have pursued financial liberalization initiatives to modernize their banking sectors These developed countries, along with two other developing countries in the region with emerging economies, Vietnam and Myanmar, are currently adopting financial liberalization programs Financial liberalization is necessary for Vietnam and Myanmar in the current international integration context, but it should not be rushed because aside from the expected benefits of financial

liberalization, it would be significantly challenging Financial liberalization will make country’s financial markets more exposed to risk factors, particularly in emerging countries One of these programs criteria was the deregulation of interest rates, which resulted in interest rate volatility However, the financial sector’s recovery has promoted the development of the banking industry, thereby gradually contributing to economic growth Furthermore, these countries' financial systems are primarily bank-based, implying that the banking sector plays a critical role in their economies (Demirgü-Kunt and Levine, 2001, 81–140) Therefore, monetary policymakers must investigate the effects of interest rates and their volatility on the BSD, particularly in the economy of Southeast Asian countries, where research is scarce

In conclusion, the author finds that study on this topic is still in its early stages and that the number of studies on interest rates and interest rate changes to BSD in Southeast Asia, particularly in Southeast Asia, is still lacking As a result,

the author decided to write a graduate thesis on the topic “The impact of interest

rate and its volatility on banking sector development: Empirical evidence from Southeast Asia”

1.2 RESEARCH OBJECTIVES AND QUESTIONS

1.2.1 Overall research objective

This thesis aims to determine the relationship between interest rate, interest rate volatility, and banking sector development of countries in Southeast Asia including Indonesia, Malaysia, Myanmar, Singapore, and Vietnam from the year

1996 to the end of 2020 Thereby, proposing suitable recommendations for banks and policymakers to support the development of the banking sector

1.2.2 Specific research objectives

The thesis has three specific objectives as follows:

 Analyzing the influence of interest rate and its volatility on banking sector development

 Assessing the impact level of interest rates and its volatility to four normal BSD indicators and a constructed component index

 Proposing recommendations for banks and monetary policymakers to strengthen and support the development of the banking sector

1.2.3 Research questions

In order to solve the research problem and achieve the above research objectives, the study presents the following three research questions:

 Do interest rate and its volatility affect banking sector development?

 How do these factors affect banking sector development?

 Which recommendations are proposed to strengthen the banking system and promote the economic growth of these countries?

1.3 RESEARCH SCOPE AND SUBJECT

1.3.1 Research subject

The research subject of the study is the impact of interest rate and its volatility on banking sector development in the economies of five Southeast Asian countries In which, the level of BSD is represented by four usual BSD indicators

including private sector (PC), liquid liabilities (LL), broad money (BM), bank deposits (BD), and one new-constructed component index based on theory and

related research

1.3.2 Research scope

The thesis has the research scope as follows:

 Scope of content: The primary goal of this thesis is to investigate the

impact of interest rates and its volatility on the development of the banking

sector in five Southeast Asian countries Clarifying, focusing on analyzing the impact of these factors From there, discuss and provide solutions and suggestions to enhance and assist the banking sector’s development

 Time range: From the beginning of the year 1996 to the end of 2020

 Spatial scope: The thesis collects secondary data from five countries

in Southeast Asia which are Indonesia, Malaysia, Myanmar, Singapore, and Vietnam

1.4 RESEARCH METHODOLOGY

To conclude this thesis, the author utilizes both qualitative and quantitative methodologies, namely the approach methods, data collection methods, and data processing methods:

 The approach methods: According to Hajilee et al (2015), their

research is the first to look into the relationship between interest rate volatility and BSD Alam and Uddin (2009) looked at the relationship between interest rate volatility and bank stock returns in fifteen developed and developing countries; Pradhan et al (2014b) defined and explained BSD; while Tuna and

Almahadin (2021) proposed "Index" as a BSD measure These studies also

serve as a foundation for deciding on a study focus on the relationship between interest rates, interest rate volatility, and banking sector development

 Data collection methods: The research draws on secondary data of

Southeast Asian countries collected from the World Bank World Development Indicators and Global Financial Development Databases However, for the period 1996 to the end of 2020, the collection of fully public data for all Southeast Asian countries remains limited As a result, only five of eleven countries were chosen since their data was sufficient for the research

 Data processing methods: First, the author performs panel unit root

tests including Levin-Lin-Chu (LLC) test and Im-Pesaran–Shin (IPS) test, especially Levin et al (2002) test for a unit-rooted process, and Im et al (2003) test for a unit-rooted discrete process To estimate the regression equations and verify some ordinary least squares (OLS) model hypotheses, the author employs the OLS regression approach on normal panel data with the Pooled OLS least squares method The author also utilizes the pooled FGLS method to estimate the above models, which will result in more efficient estimators if the model is correctly specified in cases where classical assumptions can be relaxed to allow heteroskedasticity across countries, cross-sectional correlation, and/or correlation overtime for the error terms (Green and Silverman, 1993, 448)

1.5 NEW CONTRIBUTIONS OF THE STUDY

1.5.1 Research gap

To the best of my knowledge, no studies except one by Tuna and Almahadin (2021) have discovered that there has a potential nonlinear relationship between

interest rates and BSD at the aggregate level In addition, they proposed "Index" as

a BSD measure when considering non-linear settings in variables However, the study of Tuna and Almahadin (2021) has not focused much on countries in Southeast Asia It can be seen that the economies of countries in Southeast Asia have developed quite rapidly in recent years, but the arrival of the COVID-19 epidemic has slowed down all trade activities and seriously affected the economy of the entire region, especially in the banking sector Central banks of countries had to lower interest rates in 2020 and maintain low-interest rates for the whole year 2021 Until now, they are still also considering making appropriate interest rate policies

Realizing the importance of the problem, the author combines the study of Tuna and Almahadin (2021) with other documents mentioned in the other sections

to investigate the relationship between interest rate and its volatility on BSD with a

series of conventional BSD measures The author will also reconstruct an indicator

named “Index” that represents BSD for selected Southeast Asian countries A

comprehensive index for BSD is created based on regularly used indicators such as

private sector (PC), liquid liabilities (LL), broad money (BM), and bank deposits (BD) Through this study, the author contributes to the general literature by

capturing the relationship between interest rate behavior and various aspects of the development of the banking sector Furthermore, any potential nonlinear relationship between interest rates and banking sector development indicators is

also considered in this thesis

1.5.2 New contributions

The thesis has significant contributions in both theoretical and practical aspects, specifically as follows:

 In empirical literature: This thesis contributes to affirming the

relationship between interest rates, interest rate fluctuations and the development of the banking sector in the economies of five Southeast Asian countries from 1996 to the end of 2020 From previous studies, the author continues to build on the knowledge in this area by documenting the relationship between interest rate behavior and a number of different aspects

of BSD Moreover, this thesis also inherits the determination of the influence

of these factors on BSD

 In terms of practice: The thesis highlights the importance of the

formal banking sector as well as the development of financial intermediaries in the growth of the financial sector and the economy The study reaffirms that both bank regulators and monetary policymakers must have a solid understanding of the banking system's sensitivity to interest rate policy This issue places a huge responsibility on policymakers, particularly in Southeast Asia, they must carefully develop their strategies to offset the negative effects of interest rate uncertainty and commence financial deepening

to enhance their banking systems as well as economic growth

1.6 FRAMEWORK OF THE RESEARCH PROCESS

A framework of the research process provides an objective view of the essay's structure The study was carried out in five steps to present a design of the research process as shown below:

 Step 1: Determine the research problem

The impact of interest rate and its volatility on banking sector development: empirical evidence from Southeast Asia

 Step 2: Construct a theoretical framework and related empirical studies

The author proposes a panel data regression model that is based on theoretical foundations and relevant empirical research Along with the secondary data set collected from reputable data sources, the author uses a quantitative analysis method with the support of STATA software

 Step 3: Collect data and information

The research utilizes secondary data from Southeast Asian countries which are collected from the World Bank World Development Indicators and Global Financial Development Databases from 1996 to the end of 2020 This dataset provides 125 observations from five countries and a twenty-five-year time series (N = 5, T = 25)

 Step 4: Perform a quantitative analysis

Data processing steps include panel unit root tests, descriptive statistics, model selection test Pooled OLS, FEM, REM, FGLS)

 Step 5: Write and complete a report

The author analyzes regression results, generates conclusions, and also provides recommendations for banks and policymakers

1.7 STRUCTURE OF THE RESEARCH

In addition to elements such as a table of contents, data lists, references, and

citations written in APA (American Psychological Association) style, the thesis is organized into five chapters:

 Chapter 1: Introduction

This chapter attempts to give an overview of the research, including the reasons for choosing the topic, the research subject, the research purpose, the object and scope of the study, the research questions, the research methodology, the structure of the research and the contribution of the topic in terms of literature and practice

 Chapter 2: Theoretical basis and overview of related studies

The author summarizes theories concerning interest rates, their volatility, the role of interest rate policy and their relationship in this chapter Simultaneously, the author also examines domestic and international research

to develop a theoretical research model The main points of chapter two were summarized and used as a foundation for chapter three's implementation

 Chapter 3: Research methodology

The purpose of Chapter three is to present the research methodology, the overall data gathering process and to describe in detail the variables used Moreover, this chapter also explains the benefits and drawbacks of each used model, thereby giving the way to run the model and research data appropriately The main points of chapter three were summarized and used as

a foundation for chapter four's implementation

 Chapter 4: Empirical results and discussion

The results of the models employed in this research are presented in this chapter, as well as how it displays the impact of interest rate and its volatility

on BSD The outcomes of the data analysis will be reviewed

 Chapter 5: Conclusions and recommendations

The author brings a broad conclusion regarding the research findings in this chapter and then makes recommendations for regulators and monetary policymakers to enhance and assist the banking sector's development

CHAPTER 2 THEORETICAL BASIS AND OVERVIEW OF

RELATED STUDIES

The author provides the essential theories of interest rates and their volatility such as the classical theory of interest, liquidity preference theory of interest, and also associates loanable funds theory in this chapter In addition, previous study evaluation results have been presented to emphasize the topic's urgency and give a foundation for developing research models and assessing research findings in the next chapters

2.1 THEORETICAL BASIS OF INTEREST RATE, INTEREST RATE VOLATILITY, AND BANKING SECTOR DEVELOPMENT

2.1.1 Concept of interest rate

According to Lê Thị Tuyết Hoa and Nguyễn Thị Nhung (2011), an interest rate is a percentage (%) that reflects the interest payable (or cost) computed on the entire loan amount over a certain time period Each unit of interest rate is regarded

as a point of interest rate So essentially, an interest rate is a metric for expressing the cost of loan capital Because of that, interest rates have a direct impact on the consumption and savings decisions of individuals, investors, and households as well

as the unemployment rate Moreover, interest rates have a significant impact on economic development and growth, particularly in the banking industry

Interest rates are classified differently based on each criterion, such as fixed interest rate and variable interest rate; short-term interest rate and long-term interest rate; State credit interest rate, commercial interest rate, and bank interest rate; discount rate, coupon rate, real interest rate, and closing interest rate The author investigates the impact of real interest rates in this research To sum up, it is the interest rate after inflation has been adjusted It is simply defined by the Fisher equation (1937) as the nominal interest rate minus the inflation rate

The role of interest rate: The interest rate is a crucial key instrument in the

economy for attracting idle money from where it is plentiful to where it is needed Notably, Lê Thị Tuyết Hoa (2011) stated that interest rate plays the following roles:

 Interest rate is a method for attracting all idle capital in the economy

by stimulating material interests Because the interest rate is a unique price for monetary capital, it must also adhere to the law of supply and demand in the market If a bank wants to raise a large amount of cash from outside sources, it raises the deposit interest rate, stimulating the customer's demand for profit Hence, the interest rate is used to control the bank's cash flow

 Interest rate is a tool used to encourage investment and economic development A reasonable interest rate encourages investors to borrow money

to increase production and business, create more products for society, and reduce unemployment It also assists to boost national income and enhance people's living standards, laying the foundation for a far more developed society

 Interest rate is used to encourage banks and businesses to operate more efficiently For bank institutions: Banks' primary function is to mobilize capital for lending, and they employ a variety of strategies to attract temporarily idle capital in society Simultaneously, banks employ effective methods of utilizing loan capital in order to maximize financial gains

 One of the methods for forecasting the economic situation is the interest rate: It is possible to estimate the state of the economy based on the situation and changes in interest rates throughout one term using a variety of elements such as profitability of investment projects, monetary situation, future economic situation, objectives of State policies Banks and corporations can then select suitable methods for their business plans based on this information

 The interest rate is a macro regulatory tool that is used to implement the country's national monetary policy objectives The central bank can use the

interest rate tool to restrain and control inflation or stimulation to limit reduction, market stabilization and stimulation of economic development

2.1.2 Concept of interest rate volatility

Thạnh Hoàng Đăng Khoa (2003) illustrated that interest rate is considered as the price of credit, which is already the price, it must be affected by the law of price

as well as the law of supply and demand He also stated that price fluctuations are

an unavoidable part of the economy Interest rate volatility has been observed in several economies Furthermore, he said that interest rate volatility is viewed as a measure of the dispersion of interest rates (or returns from any other financial instrument) over a given period (usually a year) The average daily, weekly, or monthly increase in interest rates is the basic measure of the interest rate volatility (Thạnh Hoàng Đăng Khoa, 2003) This has the ability to affect a country's economic performance For example, the cost of doing business in several countries around the world fluctuated significantly following the oil shocks of 1974 and 1979, including the United States, creating volatility in interest rates At that time, consumers had to spend higher prices on products and services because of high oil prices This led to high inflation rates and was further exacerbated by oil shortages The actual high inflation rate at that time caused uncertainty about the future inflation rate As a result, considerable fluctuations in actual and predicted inflation rates bring about interest rate volatilities

According to Garner (1986), one of the key variables that cause interest rate volatility is the business cycle For example, a recession reduces real output, which has an impact on interest rates since the level of economic activity influences demand for money and credit As a result, significant economic shocks frequently lead to considerable volatility Interest rate volatility is influenced by both real and inflation rates The GDP deflator is one of the inflation indicators If the GDP deflator rises or decreases sufficiently, interest rates are likely to change The

loanable fund’s theory explains why interest rates are so volatile and will be presented clearly in the following sections

In addition, changes in interest rates have an impact on investment demands, import and export activities, and the gross national product Interest rate changes also have an impact on consumer demand, therefore they have aided in the regulation of production and consumption, as well as the supply and demand for goods Garner (1986) stated that though interest rate uncertainty may not affect the demand for money, larger interest rate fluctuations can have a significant effect on the macroeconomy

2.1.3 The relationship between interest rate and different aspects of the banking industry

Another body of research looks into whether the link between interest rates and other elements of the banking industry, such as profitability, stock market returns, liquidity, financial stress, and the interest rate's functional role in the economy, is nonlinear rather than linear Especially, Ballester et al (2011) used parametric and non-parametric models to investigate the linear and nonlinear relationships between interest rate changes and stock market returns in the Spanish banking industry In terms of nonlinear exposure, their research revealed that the Spanish banking industry was exposed to interest rate risk Similar findings were also discovered by Trujillo-Ponce (2013) when it came to the association between bank size and profitability

Moreover, Boric et al (2017) looked examined the impact of monetary policy, as measured by the short-term interest rate, on banking profitability in 14 developed nations from 1995 to 2012 They claimed that the link between interest rates and bank profitability should not increase monotonously, but could be concave

or convex depending on certain conditions The authors also went into great length

on the theoretical underpinnings of such a nonlinear relationship For the examined nations, their empirical findings indicate the existence of a concave connection

between interest rates and bank profitability As a result of this nonlinear relationship, changes in interest rates have a greater impact on bank profitability at low levels when it is near zero

Furthermore, Sun et al (2017) discovered a nonlinear association between non-interest income (NII) and bank performance in China in another research Zhang and Deng (2020) investigated the link between interest rate and bank liquidity for the same nation using a quadratic functional form Their findings back with the idea that there is a nonlinear relationship between bank liquidity and interest rate liberalization They reported that this association appears to be convex and U-shaped

In addition, Saldas (2017) focused on the impact of monetary policy and financial stress on economic production in numerous advanced nations The empirical findings revealed that the connection between interest rate, as a proxy for monetary policy, and financial stress was nonlinear, resulting in a reduction in the selected nations' economic output

In recent years, Montes and P'erez (2018) utilized time-series data from 2000

to 2016 to examine the effects of interest rate fluctuations on profit indicators in Spain's banking industry Their findings imply that there is a nonlinear correlation between interest rates and bank performance Using a set of time series data, Bahruddin and Masih (2018) explored the correlation between the non-performing loans ratio (NPLR) and the lending interest rate (LIR) by manipulating the autoregressive distributed lag (NARDL) technique The authors discovered a nonlinear relationship between LIR and NPLR in Malaysia's banking industry They claimed that this relation could constrain the banking sector's functional role, which would have negative consequences for economic growth

Avisoa et al (2018) investigated the influence of interest rates on several banking features of a group of big multinational banks in 25 countries in the years

2015 and 2016 Their findings support the idea that it exists a nonlinear relationship between bank performance and interest rates The authors also emphasized the

reduction of operating efficiency in banking organizations because of interest rate volatility, which would have a negative impact on the banking sector's functional position in an economy

2.1.4 The relationship between interest rate volatility and banking sector development (BSD)

Hajilee et al (2015) claimed that their research is the first to look at the association between interest rate volatility and BSD In most developing nations, their findings revealed a negative relationship between interest rate volatility and BSD Nevertheless, in the case of Malaysia and Indonesia, the researchers concluded that the correlation is insignificant Additionally, BSD is also described

by Pradhan et al (2014b) as "a process of improving the quantity, quality, and efficiency of banking services" They further noted that the BSD process involves several mutual-action activities that are difficult to capture with a single indicator For example, the higher the deposit money banks' assets are, the larger the financial institutions are in relation to the economy's size Therefore, I believe that additional research is urgently needed to explore the relationship between interest rate behavior and BSD through a more complete indicator instead of using four basic

indicators (PC, LL, BM, BD) This index integrates various development parameters

of the banking industry and will be discussed in more detail in section 3.2

2.2 THEORETICAL BACKGROUND

2.2.1 Classical Theory of Interest

British economists invented the classical interest rate theory in the 18th and 19th centuries, which was revised by Austrian economist Bohm Bawek (1851 – 1914) in the early 20th century and further developed by Irving Fisher (1867 – 1947) It is also the fundamental theory for Keynesian liquidity preference theory of interest This theory also shows that the interest rate depends not only on the supply

of savings from households, firms, and the government but also on the demand for investment capital

This theory states that the interest rate has an inverse relationship with the demand for investment capital, in other words, the higher the interest rate, the lower the demand for investment capital and vice versa Based on figure 2.1, it can be seen that interest rates in the financial market are determined by the combination of the supply of savings and the demand for investment capital When the supply of savings in financial markets balances the demand for investment capital, the equilibrium interest rate is established

Figure 2.1 Classical Theory of Interest

The traditional interest rate theory highlights the public's saving habits and the necessity for capital to invest in manufacturing It can be seen that because these factors do not vary rapidly, the classical theory of interest rates is thought to be the classical theory of interest rates is said to be suitable for describing long-term

interest rates

2.2.2 Liquidity Preference Theory of Interest

The short-run theory of interest rates, also popularly known as the liquidity theory of interest rates, was founded in the 1930s by British economist - John

Maynard Keynes Based on figure 2.2, it can be seen that the short-run equilibrium

interest rate is determined by the interaction between aggregate demand and aggregate money supply Keynes (1937) implied that interest rates are set when the supply and demand for money are equal The aggregate demand for all three needs:

transaction, supply, and speculation are called demand The interest rate is determined by the balance between the supply and aggregate demand for money according to this theory

When the market rate of interest is high, people anticipate it to decline in the future, and bond and security prices will rise This is how Keynes' analysis accounts for the form of the liquidity preference curve Bonds and securities are consequently appealing to them since they expect capital gains from them, but cash is less appealing, resulting in reduced demand for cash

People predict that the current rate will increase in the future or that the asset price will decrease if the current rate is low People are more interested in cash because holding bonds and stocks carries the risk of losing money, so they seek a higher amount of cash Therefore, the liquidity incentive will be low and the current interest rate will be high In other words, money demand is negatively related to expected fluctuations in interest rates

Figure 2.2 Liquidity Preference Theory of Interest

The liquidity theory of interest rates, like the classical approach, has several shortcomings Liquidity theory, as can be shown, is just a short-term approach to interest rate determination because interest rates are impacted in the long run by changes in income levels, prices, and inflation Furthermore, following to Wright (2012), an economy cannot have a steady equilibrium interest rate unless it has a

consistent level of income, savings, and investment

2.2.3 Loanable funds theory

Knut Wicksell (1851-1926) who was a well-known Swedish economist, expounded the Neo-classical theory which was named the Loanable fund theory In addition, Ohlin (1933), Robertson (1940), and other new-classical economists also contributed to the development of this theory It was acknowledged widely before British economist John Maynard Keynes's work (1883-1946) The classical savings and investment theory of interest rate is the foundation for the loanable funds theory

of interest rate

Figure 2.3 Loanable funds theory graph

According to the loanable funds theory of interest, interest rates are governed

by the supply and demand of loanable funds in capital markets Especially, this theory is based on the financial flows of different sectors of the economy including

the supply and demand for loan funds from enterprises, households, and governments The loanable funds theory of interest implies that long-term interest rates are governed by investments and savings, while short-term rates are influenced

by financial and monetary conditions in the economy By looking at the aggregate supply and demand of the aforementioned regions, this hypothesis attempts to explain interest rate fluctuations

Based on figure 2.3, it can be seen that at some point in the capital market, the supply and demand for loanable funds jointly establish an equilibrium, which establishes the equilibrium interest rate of the capital market Then for some reason the supply or demand for loanable funds changes:

- If it increases, the supply or demand curve shifts to the right

- If it decreases, the supply or demand curve shifts to the left

 This leads to the market losing its equilibrium

At this time, due to price-interest rate pressure, the demand or supply curve will change to establish a new equilibrium It can be seen that if supply increases, interest rates fall, and demand for loans increases, this pressure shifts the demand curve to the right to establish a new equilibrium Conversely, if supply decreases, interest rates rise, demand for loans falls, and the demand curve shifts to the left by price-interest rate pressure, creating a new equilibrium

2.3 THE RELEVANT EMPIRICAL STUDIES

Because there are few research topics on the impact of interest rates and volatility on banking sector development, evaluating the impact of interest rates and volatility on BSD is a critical and urgent issue, especially at a time when the world

is suffering from the devastating consequences of the COVID-19 epidemic It can

be seen that up to now there have been quite a few research works related to this issue, the most notable of which are:

2.3.1 Vietnamese researches

According to Thạnh Hoàng Đăng Khoa (2003), interest rate fluctuations are

an inevitable part of the economy The author focused on examining the interest rate management mechanism of the State Bank of Vietnam in each certain period as well

as presented a perspective on Viet Nam’s interest rate liberalization process The author also underlined the necessity of interest rate liberalization and offers strategies to mitigate interest rate risk in bank operations

Đinh Thị Thu Hằng (2018) examined the effect and direction of interest rates

on economic growth in Southeast Asian countries To measure the impact of interest rates on economic growth in Southeast Asian countries, the author devised a quantitative study model The author employed the estimate approach for the regression model using balanced panel data, which included Pooled OLS model, FEM model, and REM model, and afterward tested and handled faults on the selected model The presence of the dependent variable's lagged variable as an independent variable produces endogeneity in the dynamic tabular model, hence the author utilized the GMM estimation method for endogenous treatment

2.3.2 English researches

Through previous empirical studies related to the topic, the author inherited from foreign studies and mainly based on the research of Tuna and Almahadin (2021) as the background research because the model research is quite relevant The author inherits the research model and uses a new survey space compared to previous studies and updates the temporal data to increase the reliability of the thesis To examine the relationship between interest rates, interest rate volatility, and the development of the banking sector, Tuna and Almahadin (2021) collected annual data from 1980 to 2014 in twelve emerging market economies around the world Their empirical results showed that when the relationship between interest rates and development indicators of the banking industry weakens at higher interest rates, it proved that interest rates had a positive impact on these indicators In

addition, they also demonstrated that interest rate volatility had a negative impact on most banking sector development (BSD) indicators, especially in emerging countries Finally, the economic growth rate has a positive effect on BSD, and when

at higher levels of income, this relationship weakens, which showed that existed a nonlinear relationship

A great number of researchers have looked into the effects of interest rates and their volatility on banking organizations from varied viewpoints The majority

of research has explored the connection between interest rate volatility and bank stock returns The empirical findings of this line of research show a negative relationship between market stock returns and interest rate movements (Alam and Uddin, 2009; Campbell, 1987; Elyasiani and Mansur, 1998; Flannery et al., 1997; Harasty and Roulet, 2000; Joseph and Vezos, 2006; Kasman et al., 2011; Papadamou and Siriopoulos, 2014; Tripathi and Ghosh, 2012; Yourougou, 1990; Zhou, 1996) Especially, Alam and Uddin (2009) evaluated the association between interest rate volatility and bank stock returns in fifteen developed and developing nations They analyzed monthly data from 1998 to 2003 using time-series approaches as well as panel data analysis Their studies demonstrated that stock market returns and interest rate volatility had a negative and significant relationship Furthermore, using autoregressive conditional heteroscedasticity in the mean (GARCH-M) model, Elyasiani and Mansur (1998) evaluated the sensitivity of US banking stock returns to changes in the interest rate and its volatility for the period

1970 – 1992 Their research shows that long-term interest rates have a considerable negative impact on stock market returns Additionally, interest rate volatility was discovered to be the principal source of banking stock return fluctuations

To discover a negative association between interest rates and stock prices in Brazil, Hsing (2004) applied the structural vector autoregressive (SVAR) model From 1999 to 2009, Kasman et al (2011) examined the dual effect of interest rate and exchange rate changes on the profitability of Turkish banks on the national stock market GARCH models and ordinary least squares (OLS) estimation methods

have been applied by the authors in their research Their findings provide evidence

of how volatility in interest rates affects the sensitivity of Turkish banking stocks Not only that, their research results confirm the conclusion of Elyasiani and Mansur (1998) that interest rate volatility is the most important predictor of stock market volatility Otherwise, Simpson and Evans (2003) manipulated the co-integration technique to investigate the sustainable relationship between interest rates, a collection of macroeconomic factors and stock profits of Australian banks As a result, they did not find any signs that showed the appearance of a co-integration relationship between short-term and long-term interest rates as well as the stock profits of banks

Based on theoretical aspects, McKinnon (1973) and Shaw (1973) mentioned the important role of interest rate policy as an indispensable tool of monetary policy during the development of the banking system The time it affects the banking sector through functional channels including pooling savings and capital channels to mobilize in investment and production areas more effectively In recent times, Naveed (2015) not only used measurement tools were interest rates but also applied the VAR method and other economic methods to assess the impact of monetary policy shocks on the banking sector in Pakistan during the period 2009 - 2013 He discovered that monetary policy shocks played an important role in the operation of conventional banks, but conversely non-conventional banks show the opposite

During the period from 1999 to 2014, Mushtaq and Siddiqui (2017) verified the relationship between bank deposits and real interest rates Annual data series for

23 Islamic and Muslim countries have been used The authors used the panel ARDL approach to prove that deposits in the bank sector are not sensitive to interest rates, especially in Islamic countries Nonetheless, in non-Muslim countries, the effect of interest rates becomes positive and has a considerable impact on the banking industry However, previous studies had shown that there is not enough convincing evidence for such a relationship For instance, Flannery (1981) used linear regression analysis to investigate the impact of interest rates on the profits of banks

in the United States He discovered that there was no significant relationship between interest rates and the performance of banks in this area Based on the analysis of asset terms and liabilities of banks in the US, he had a positive assessment of the reasonable risk management policies of these banks and this was also the reason for explaining his research results Flannery (1983) also found that the expenses and revenue of large banks were not affected by changes in market interest rates in another study Mitchell (1989) has also created models to check the level of interest rate risks of banks from 1976 to 1983 His finding showed that the interest rate fluctuations were less affected by the banking industry because banks had applied strategies to effectively manage and control risks

It can be seen that most recent studies focus on investigating the impact of uncertainty of interest rates on organizations and financial systems and also emphasizing the strong spillover effects of interest rates volatility on an international scope Wang (2020), for example, declares that unforeseen changes in policy interest rates are the main driving force of the spillover effects of interest rates on the foreign stock market Moreover, according to Khan et al (2020), the change in interest rates caused fluctuations in the stock market index and the instability of the financial system In the case of emerging economies, Koech and Maina (2020) considered the influence of interest rates on loan repayments The detection of these authors indicates that the repayment capacity of borrowers, as well as borrower’s interest payment, has been damaged by the interest rate fluctuations This will increase the level of credit risk of banking organizations, endangering financial stability and minimizing profits Interest fluctuations, according to Hatmanu et al (2020), is an indispensable element that affects the economic development of the Romanian nation Their findings indicated that European Union policy makers should take significant efforts to develop general monetary policy effectively to members of the EURO common currency area

To sum up, while there were many studies on the subject of interest rate volatility, each one reflected diverse opinions on its impact on the banking sector's

development Each study used different methods and strategies, resulting in different solutions with distinct characteristics that will help policymakers make appropriate decisions by enhancing the efficiency of the banking sector On the basis of approaching and inheriting previous studies, the author delves deeply into, collects data, analyzes, processes data, assesses, and provides recommendations based on the approach and inheritance of past studies, with the goal of contributing

to the development of the banking industry in Southeast Asia As a result, when compared to earlier studies, the author's research from 1996 to the end of 2020 has distinct characteristics in terms of time scope and research space

CHAPTER 3 RESEARCH METHODOLOGY

The purpose of Chapter 3 is to present the research methodology, the overall data gathering process and to describe in detail the variables used The analytical methods and standards used to check the fit will be presented in Chapter 3 and serve for running the model and giving the results for the next chapter

3.1 DATA SOURCE

In table 3.1, it can be seen that the sample of this research includes five countries in Southeast Asia including Indonesia, Malaysia, Myanmar, Singapore and Vietnam for the period 1996 to the end of 2020 The whole year 2021 was not included in the study period due to data limitations for some of the above countries

Research data is secondary data collected from the World Bank World Development Indicators and Global Financial Development Databases However, for the period 1996 to the end of 2020, the collection of fully public data for all Southeast Asian countries remains limited As a result, only five of eleven countries were chosen since their data was sufficient for the research To clarify, Indonesia, Malaysia, and Vietnam are all developing/ emerging countries; only Singapore is a developed/ advanced country; and Myanmar is a least developed country The economies of these countries are also clearly classified according to table 3.1, specifically, Indonesia and Malaysia have upper-middle-income economies; Vietnam and Myanmar have lower-middle-income economies while only Singapore has a high-income economy

In the period 1996 to the end of 2020, it can be seen that the global banking industry underwent crisis times due to the general impact of the global financial crisis originating from the United States Therefore, the author did not exclude the period of the financial crisis from the sample to ensure the Law of Large Numbers

in quantitative research because the database is still relatively limited (covering only five countries over a twenty-five-year timeframe)

Table 3.1 List of countries used in the research

Country National flag Country group Economy

Indonesia Developing/ Emerging

Newly industrialized country

Upper-middle income

Malaysia Developing/ Emerging

Newly industrialized country

Upper-middle income

Myanmar Least developed Lower-middle

income

Singapore Developed/ Advanced High-income

Vietnam Developing/ Emerging Lower-middle

income

Source: Author's own synthesis from World Bank Country and Lending Groups

and World Economic Outlook Database

3.2 DESCRIPTION OF VARIABLE

Based on figure 3.1, it can be seen that an economic model determines whether dependent and independent/explanatory variables are positively or negatively related The relation between variables is positive when the dependent variable shifts in the same direction as the independent/explanatory variable Conversely, the relationship is negative when the value of the dependent variable increases (decreases) and when the value of the independent/explanatory variable declines (grows) The below figure illustrates the relationship between variable types in more detail:

Figure 3.1 The relationship between variable types

Source: Performed by the author

3.2.1 Dependent variable

Because the goal of this study is to consider the impact of interest rates and their fluctuations on the banking industry in the sample countries so the dependent variable of the research will be representative variables for BSD Based on the previous documents presented in Chapter two, it can be seen that the four variables

are regularly used for BSD as bank credit for the private sector (PC), liquid liabilities (LL), broad money (BM) and bank deposits (BD), all of them are

expressed by the percentage of GDP In addition to these basic factors, the current study also manipulates the principal component analysis (PCA) to build a comprehensive indicator for BSD which is named "Index" This index is built using

the basic elements (PC, LL, BM and BD) of BSD

Domestic credit to private sector (PC)

Because the private sector (PC) ratio reflects the operation of deposit

organizations, it is used to measure the growth of the banking system in countries This is also one of the most comprehensive indicators as well as leading compared

to other indicators of the development of financial intermediaries This ratio represents the importance of the banking industry officially to the economy

Dependent variable